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Grounded Theory-Based User Needs Mining and Its Impact on APP Downloads: Exampled With WeChat APP

Software development is an iterative process from designing to implementation, and to testing, in which product development staff should be closely integrated with users. Satisfying user needs effectively is often the pain point for developers. In order to alleviate this, this paper manages to estab...

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Autores principales: Chen, Tinggui, Zhang, Chu, Yang, Jianjun, Cong, Guodong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9237435/
https://www.ncbi.nlm.nih.gov/pubmed/35774947
http://dx.doi.org/10.3389/fpsyg.2022.875310
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author Chen, Tinggui
Zhang, Chu
Yang, Jianjun
Cong, Guodong
author_facet Chen, Tinggui
Zhang, Chu
Yang, Jianjun
Cong, Guodong
author_sort Chen, Tinggui
collection PubMed
description Software development is an iterative process from designing to implementation, and to testing, in which product development staff should be closely integrated with users. Satisfying user needs effectively is often the pain point for developers. In order to alleviate this, this paper manages to establish the quantitative connection between users' online reviews and APP (Application Program) downloads. By analyzing user online comments, companies can dig out user needs and preferences. This could benefit them by making accurate market positioning of their APP products, and therefore iteratively innovating products based on user needs, which hopefully will increase the volume of APP downloads. This paper regards WeChat APP during 47 updates periods as the research object. Based on Grounded Theory, user needs are extracted after data cleaning. Next, by using semantic analysis and word frequency analysis, we are able to obtain the implicit feedbacks such as emotion tendency, satisfaction and requirements lie under online reviews. Then, we construct a quantile regression model to study the impact of users' online reviews on downloads based on the influencing factors we extracted so as to provide a decision basis for enterprises to iteratively update their products. Results show that: (1) Generally speaking, needs of WeChat users mainly focus on performance, reliability, usability, functional deficiency, functional insufficiency, and system adaptability; (2) For those APP versions with relatively fewer downloads, user needs are mostly about functional deficiency, followed by functional insufficiency, performance, usability, and system adaptability. At this stage, it is found out that users' emotion tendency and user satisfaction significantly affect the volume of downloads; (3) When the volume of APP downloads is moderate, the user needs are functional deficiency, functional insufficiency, and system adaptability. While under this circumstances, users' star ratings have a significant impact on downloads; (4) In addition, when the volume of App downloads is high, user needs are performance, usability, and system adaptability. Our methods effectively extract users' requirements from online reviews and then successfully build up the quantitative connection between the implicit feedbacks from those requirements and APP downloads.
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spelling pubmed-92374352022-06-29 Grounded Theory-Based User Needs Mining and Its Impact on APP Downloads: Exampled With WeChat APP Chen, Tinggui Zhang, Chu Yang, Jianjun Cong, Guodong Front Psychol Psychology Software development is an iterative process from designing to implementation, and to testing, in which product development staff should be closely integrated with users. Satisfying user needs effectively is often the pain point for developers. In order to alleviate this, this paper manages to establish the quantitative connection between users' online reviews and APP (Application Program) downloads. By analyzing user online comments, companies can dig out user needs and preferences. This could benefit them by making accurate market positioning of their APP products, and therefore iteratively innovating products based on user needs, which hopefully will increase the volume of APP downloads. This paper regards WeChat APP during 47 updates periods as the research object. Based on Grounded Theory, user needs are extracted after data cleaning. Next, by using semantic analysis and word frequency analysis, we are able to obtain the implicit feedbacks such as emotion tendency, satisfaction and requirements lie under online reviews. Then, we construct a quantile regression model to study the impact of users' online reviews on downloads based on the influencing factors we extracted so as to provide a decision basis for enterprises to iteratively update their products. Results show that: (1) Generally speaking, needs of WeChat users mainly focus on performance, reliability, usability, functional deficiency, functional insufficiency, and system adaptability; (2) For those APP versions with relatively fewer downloads, user needs are mostly about functional deficiency, followed by functional insufficiency, performance, usability, and system adaptability. At this stage, it is found out that users' emotion tendency and user satisfaction significantly affect the volume of downloads; (3) When the volume of APP downloads is moderate, the user needs are functional deficiency, functional insufficiency, and system adaptability. While under this circumstances, users' star ratings have a significant impact on downloads; (4) In addition, when the volume of App downloads is high, user needs are performance, usability, and system adaptability. Our methods effectively extract users' requirements from online reviews and then successfully build up the quantitative connection between the implicit feedbacks from those requirements and APP downloads. Frontiers Media S.A. 2022-06-14 /pmc/articles/PMC9237435/ /pubmed/35774947 http://dx.doi.org/10.3389/fpsyg.2022.875310 Text en Copyright © 2022 Chen, Zhang, Yang and Cong. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Chen, Tinggui
Zhang, Chu
Yang, Jianjun
Cong, Guodong
Grounded Theory-Based User Needs Mining and Its Impact on APP Downloads: Exampled With WeChat APP
title Grounded Theory-Based User Needs Mining and Its Impact on APP Downloads: Exampled With WeChat APP
title_full Grounded Theory-Based User Needs Mining and Its Impact on APP Downloads: Exampled With WeChat APP
title_fullStr Grounded Theory-Based User Needs Mining and Its Impact on APP Downloads: Exampled With WeChat APP
title_full_unstemmed Grounded Theory-Based User Needs Mining and Its Impact on APP Downloads: Exampled With WeChat APP
title_short Grounded Theory-Based User Needs Mining and Its Impact on APP Downloads: Exampled With WeChat APP
title_sort grounded theory-based user needs mining and its impact on app downloads: exampled with wechat app
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9237435/
https://www.ncbi.nlm.nih.gov/pubmed/35774947
http://dx.doi.org/10.3389/fpsyg.2022.875310
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